牛奶的中红外光谱相关变量遗传参数估计
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摘要
旨在探究牛奶原始中红外光谱相关变量的遗传规律。本研究收集北京三元绿荷某牛场1 822头荷斯坦牛生产性能测定数据、中红外光谱数据和系谱数据,使用R语言(v3.51)、SAS(v9.2)、DMU(v6.0)等软件进行主成分分析和遗传参数估计,遗传参数估计使用的动物模型考虑了测定月份、胎次和泌乳天数的固定效应及个体加性遗传效应、永久环境效应的随机效应。结果表明,80%以上中红外光谱变量之间的相关系数达0.500～1.000,且3 574～3 521 cm~(-1)和3 630～3 618 cm~(-1)区域的变量变异程度较高。对中红外光谱的每个波数进行遗传参数估计,大部分波数的遗传力集中于0.010～0.030之间,处于中高遗传力的波数占比约为7%;随遗传力提高,吸光度增大、透射率降低,且变异系数降低。中红外光谱数据可用于探究牛奶成分的遗传规律,从遗传角度提高奶牛质量,为种牛选择提供参考。
This study aimed to investigate the genetic laws of the variables related to the original mid-infrared spectrometry(MIRS) of cow milk. DHI, mid-infrared spectral data and pedigree data were obtained from 1 822 Holstein dairy cows owned by farm of Beijing Sunlon Livestock Development Co., Ltd. Principal component analysis and genetic parameter estimation were performed using the R language(v3.51), SAS(v9.2) and DMU(v6.0), the animal model used for genetic parameter estimation taken into account the fixed effects including the testing months, parity and days in milk and random effects including additive genetic effect and permanent environmental effect. The results showed that the correlation coefficient among more than 80% of the wavenumbers of mid-infrared spectrometry ranged from 0.500 to 1.000, and the variation coefficients of the wavenumbers in region 3 574-3 521 cm~(-1) and 3 630-3 618 cm~(-1) were higher. The heritability of the most wavenumbers of MIRS data were mostly between 0.010 and 0.030, and the proportion of wavenumbers with medium and high heritabilities was about 7%. With the increase of heritability, the absorption increased, the transmittance and CV decreased. The genetic law of milk components can be better understood through the genetic analysis of the original MIRS data obtained from DHI samples, in order to improve the quality of milk and provide reference for cattle breeding.
This study aimed to investigate the genetic laws of the variables related to the original mid-infrared spectrometry(MIRS) of cow milk. DHI, mid-infrared spectral data and pedigree data were obtained from 1 822 Holstein dairy cows owned by farm of Beijing Sunlon Livestock Development Co., Ltd. Principal component analysis and genetic parameter estimation were performed using the R language(v3.51), SAS(v9.2) and DMU(v6.0), the animal model used for genetic parameter estimation taken into account the fixed effects including the testing months, parity and days in milk and random effects including additive genetic effect and permanent environmental effect. The results showed that the correlation coefficient among more than 80% of the wavenumbers of mid-infrared spectrometry ranged from 0.500 to 1.000, and the variation coefficients of the wavenumbers in region 3 574-3 521 cm~(-1) and 3 630-3 618 cm~(-1) were higher. The heritability of the most wavenumbers of MIRS data were mostly between 0.010 and 0.030, and the proportion of wavenumbers with medium and high heritabilities was about 7%. With the increase of heritability, the absorption increased, the transmittance and CV decreased. The genetic law of milk components can be better understood through the genetic analysis of the original MIRS data obtained from DHI samples, in order to improve the quality of milk and provide reference for cattle breeding.
引文
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[15] SOYEURT H,BRUWIER D,ROMNEE J M,et al.Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry[J].J Dairy Sci,2009,92(6):2444-2454.
[16] GRELET C,BASTIN C,GELé M,et al.Development of Fourier transform mid-infrared calibrations to predict acetone,β-hydroxybutyrate,and citrate contents in bovine milk through a European dairy network[J].J Dairy Sci,2016,99(6):4816-4825.
[17] MCPARLAND S,BANOS G,WALL E,et al.The use of mid-infrared spectrometry to predict body energy status of Holstein cows[J].J Dairy Sci,2011,94(7):3651-3661.
[18] MCPARLAND S,BANOS G,MCCARTHY B,et al.Validation of mid-infrared spectrometry in milk for predicting body energy status in Holstein-Friesian cows[J].J Dairy Sci,2012,95(12):7225-7235.
[19] MCPARLAND S,LEWIS E,KENNEDY E,et al.Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows[J].J Dairy Sci,2014,97(9):5863-5871.
[20] LAINé A,BASTIN C,THERON L,et al.Potential of fine milk composition for cow udder health management[C]//Proceedings of the 39th ICAR Conference,Berlin.Germany:ICAR,2014.
[21] DEHARENG F,DELFOSSE C,FROIDMONT E,et al.Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows[J].Animal,2012,6(10):1694-1701.
[22] FLEMING A,SCHENKEL F S,KOECK A,et al.Heritabilities of measured and mid-infrared predicted milk fat globule size,milk fat and protein percentages,and their genetic correlations[J].J Dairy Sci,2017,100(5):3735-3741.
[23] NARAYANA S G,SCHENKEL F S,FLEMING A,et al.Genetic analysis of groups of mid-infrared predicted fatty acids in milk[J].J Dairy Sci,2017,100(6):4731-4744.
[24] FLEMING A,SCHENKEL F S,MALCHIODI F,et al.Genetic correlations of mid-infrared-predicted milk fatty acid groups with milk production traits[J].J Dairy Sci,2018,101(5):4295-4306.
[25] HEIN L,S?RENSEN L P,KARGO M,et al.Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations[J].J Dairy Sci,2018,101(3):2148-2157.
[26] 钟海庆.红外光谱法入门[M].北京:化学工业出版社,1984:1-4.ZHONG H Q.Introduction to infrared spectroscopy[M].Beijing:Chemical Industry Press,1984:1-4.(in Chinese)
[27] 董利锋,YAN T H,屠焰,等.中红外光谱技术在牛奶营养物质预测及奶牛相关特性分析上的应用[J].动物营养学报,2016,28(2):326-334.DONG L F,YAN T H,TU Y,et al.Applicationof mid-infrared spectrometry in milk nutrient components prediction and related traits analysis of dairy cows[J].Chinese Journal of Animal Nutrition,2016,28(2):326-334.(in Chinese)
[28] 何晓群.多元统计分析[M].2版.北京:中国人民大学出版社,2008:152-167.HE X Q.Multivariate statistical analysis[M].2nd ed.Beijing:China Renmin University Press,2008:152-167.(in Chinese)
[29] ZAALBERG R M,SHETTY N,JANSS L,et al.Genetic analysis of Fourier transform infrared milk spectra in Danish Holstein and Danish Jersey[J].J Dairy Sci,2019,102(1):503-510.
[30] 刘澳星,郭刚,王雅春,等.中国荷斯坦牛初产日龄遗传评估及全基因组关联分析[J].畜牧兽医学报,2015,46(3):373-381.LIU A X,GUO G,WANG Y C,et al.Genetic analysis and genome wide association studies for age at first calving in Chinese Holsteins[J].Acta Veterinaria et Zootechnica Sinica,2015,46(3):373-381.(in Chinese)
[31] SOYEURT H,MISZTAL I,GENGLER N.Genetic variability of milk components based on mid-infrared spectral data[J].J Dairy Sci,2010,93(4):1722-1728.
[32] KAROUI R,MOUAZEN A M,DUFOUR é,et al.A comparison and joint use of NIR and MIR spectroscopic methods for the determination of some parameters in European Emmental cheese[J].Eur Food Res Technol,2006,223(1):44-50.
[33] COATES J.Interpretation of infrared spectra,a practical approach[M]//MEYERS R A.Encyclopedia of Analytical Chemistry.Chichester:Wiley,2006:4-15.
[34] SIVAKESAVA S,IRUDAYARAJ J.Rapid determination of tetracycline in milk by FT-MIR and FT-NIR spectroscopy[J].J Dairy Sci,2002,85(3):487-493.
[35] DUFOUR E,MAZEROLLES G,DEVAUX M F,et al.Phase transition of triglycerides during semi-hard cheese ripening[J].Int Dairy J,2000,10(1-2):81-93.
[36] BITTANTE G,CECCHINATO A.Genetic analysis of the Fourier-transform infrared spectra of bovine milk with emphasis on individual wavelengths related to specific chemical bonds[J].J Dairy Sci,2013,96(9):5991-6006.
[37] DAGNACHEW B S,KOHLER A,?DN?Y T.Genetic and environmental information in goat milk Fourier transform infrared spectra[J].J Dairy Sci,2013,96(6):3973-3985.
[2] PEREIRA P C.Milk nutritional composition and its role in human health[J].Nutrition,2014,30(6):619-627.
[3] ETZION Y,LINKER R,COGAN U,et al.Determination of protein concentration in raw milk by mid-infrared fourier transform infrared/attenuated total reflectance spectroscopy[J].J Dairy Sci,2004,87(9):2779-2788.
[4] BONFATTI V,DI MARTINO G,CARNIER P.Effectiveness of mid-infrared spectroscopy for the prediction of detailed protein composition and contents of protein genetic variants of individual milk of Simmental cows[J].J Dairy Sci,2011,94(12):5776-5785.
[5] SOYEURT H,DARDENNE P,GILLON A,et al.Variation in fatty acid contents of milk and milk fat within and across breeds[J].J Dairy Sci,2006,89(12):4858-4865.
[6] SOYEURT H,COLINET F G,ARNOULD V M R,et al.Genetic variability of lactoferrin content estimated by mid-infrared spectrometry in bovine milk[J].J Dairy Sci,2007,90(9):4443-4450.
[7] SANTOS P M,PEREIRA-FILHO E R,RODRIGUEZ-SAONA L E.Rapid detection and quantification of milk adulteration using infrared microspectroscopy and chemometrics analysis[J].Food Chem,2013,138(1):19-24.
[8] SOYEURT H,DARDENNE P,DEHARENG F,et al.Estimating fatty acid content in cow milk using mid-infrared spectrometry[J].J Dairy Sci,2006,89(9):3690-3695.
[9] SOYEURT H,DEHARENG F,GENGLER N,et al.Mid-infrared prediction of bovine milk fatty acids across multiple breeds,production systems,and countries[J].J Dairy Sci,2011,94(4):1657-1667.
[10] FERRAND-CALMELS M,PALHIèRE I,BROCHARD M,et al.Prediction of fatty acid profiles in cow,ewe,and goat milk by mid-infrared spectrometry[J].J Dairy Sci,2014,97(1):17-35.
[11] DE MARCHI M,BONFATTI V,CECCHINATO A,et al.Prediction of protein composition of individual cow milk using mid-infrared spectroscopy[J].Ital J Anim Sci,2010,8(S2):399-401.
[12] DE MARCHI M,TOFFANIN V,CASSANDRO M,et al.Prediction of coagulating and noncoagulating milk samples using mid-infrared spectroscopy[J].J Dairy Sci,2013,96(7):4707-4715.
[13] DE MARCHI M,FAGAN C C,O'DONNELL C P,et al.Prediction of coagulation properties,titratable acidity,and pH of bovine milk using mid-infrared spectroscopy[J].J Dairy Sci,2009,92(1):423-432.
[14] TOFFANIN V,DE MARCHI M,LOPEZ-VILLALOBOS N,et al.Effectiveness of mid-infrared spectroscopy for prediction of the contents of calcium and phosphorus,and titratable acidity of milk and their relationship with milk quality and coagulation properties[J].Int Dairy J,2015,41:68-73.
[15] SOYEURT H,BRUWIER D,ROMNEE J M,et al.Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry[J].J Dairy Sci,2009,92(6):2444-2454.
[16] GRELET C,BASTIN C,GELé M,et al.Development of Fourier transform mid-infrared calibrations to predict acetone,β-hydroxybutyrate,and citrate contents in bovine milk through a European dairy network[J].J Dairy Sci,2016,99(6):4816-4825.
[17] MCPARLAND S,BANOS G,WALL E,et al.The use of mid-infrared spectrometry to predict body energy status of Holstein cows[J].J Dairy Sci,2011,94(7):3651-3661.
[18] MCPARLAND S,BANOS G,MCCARTHY B,et al.Validation of mid-infrared spectrometry in milk for predicting body energy status in Holstein-Friesian cows[J].J Dairy Sci,2012,95(12):7225-7235.
[19] MCPARLAND S,LEWIS E,KENNEDY E,et al.Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows[J].J Dairy Sci,2014,97(9):5863-5871.
[20] LAINé A,BASTIN C,THERON L,et al.Potential of fine milk composition for cow udder health management[C]//Proceedings of the 39th ICAR Conference,Berlin.Germany:ICAR,2014.
[21] DEHARENG F,DELFOSSE C,FROIDMONT E,et al.Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows[J].Animal,2012,6(10):1694-1701.
[22] FLEMING A,SCHENKEL F S,KOECK A,et al.Heritabilities of measured and mid-infrared predicted milk fat globule size,milk fat and protein percentages,and their genetic correlations[J].J Dairy Sci,2017,100(5):3735-3741.
[23] NARAYANA S G,SCHENKEL F S,FLEMING A,et al.Genetic analysis of groups of mid-infrared predicted fatty acids in milk[J].J Dairy Sci,2017,100(6):4731-4744.
[24] FLEMING A,SCHENKEL F S,MALCHIODI F,et al.Genetic correlations of mid-infrared-predicted milk fatty acid groups with milk production traits[J].J Dairy Sci,2018,101(5):4295-4306.
[25] HEIN L,S?RENSEN L P,KARGO M,et al.Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations[J].J Dairy Sci,2018,101(3):2148-2157.
[26] 钟海庆.红外光谱法入门[M].北京:化学工业出版社,1984:1-4.ZHONG H Q.Introduction to infrared spectroscopy[M].Beijing:Chemical Industry Press,1984:1-4.(in Chinese)
[27] 董利锋,YAN T H,屠焰,等.中红外光谱技术在牛奶营养物质预测及奶牛相关特性分析上的应用[J].动物营养学报,2016,28(2):326-334.DONG L F,YAN T H,TU Y,et al.Applicationof mid-infrared spectrometry in milk nutrient components prediction and related traits analysis of dairy cows[J].Chinese Journal of Animal Nutrition,2016,28(2):326-334.(in Chinese)
[28] 何晓群.多元统计分析[M].2版.北京:中国人民大学出版社,2008:152-167.HE X Q.Multivariate statistical analysis[M].2nd ed.Beijing:China Renmin University Press,2008:152-167.(in Chinese)
[29] ZAALBERG R M,SHETTY N,JANSS L,et al.Genetic analysis of Fourier transform infrared milk spectra in Danish Holstein and Danish Jersey[J].J Dairy Sci,2019,102(1):503-510.
[30] 刘澳星,郭刚,王雅春,等.中国荷斯坦牛初产日龄遗传评估及全基因组关联分析[J].畜牧兽医学报,2015,46(3):373-381.LIU A X,GUO G,WANG Y C,et al.Genetic analysis and genome wide association studies for age at first calving in Chinese Holsteins[J].Acta Veterinaria et Zootechnica Sinica,2015,46(3):373-381.(in Chinese)
[31] SOYEURT H,MISZTAL I,GENGLER N.Genetic variability of milk components based on mid-infrared spectral data[J].J Dairy Sci,2010,93(4):1722-1728.
[32] KAROUI R,MOUAZEN A M,DUFOUR é,et al.A comparison and joint use of NIR and MIR spectroscopic methods for the determination of some parameters in European Emmental cheese[J].Eur Food Res Technol,2006,223(1):44-50.
[33] COATES J.Interpretation of infrared spectra,a practical approach[M]//MEYERS R A.Encyclopedia of Analytical Chemistry.Chichester:Wiley,2006:4-15.
[34] SIVAKESAVA S,IRUDAYARAJ J.Rapid determination of tetracycline in milk by FT-MIR and FT-NIR spectroscopy[J].J Dairy Sci,2002,85(3):487-493.
[35] DUFOUR E,MAZEROLLES G,DEVAUX M F,et al.Phase transition of triglycerides during semi-hard cheese ripening[J].Int Dairy J,2000,10(1-2):81-93.
[36] BITTANTE G,CECCHINATO A.Genetic analysis of the Fourier-transform infrared spectra of bovine milk with emphasis on individual wavelengths related to specific chemical bonds[J].J Dairy Sci,2013,96(9):5991-6006.
[37] DAGNACHEW B S,KOHLER A,?DN?Y T.Genetic and environmental information in goat milk Fourier transform infrared spectra[J].J Dairy Sci,2013,96(6):3973-3985.
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